Taylor Swift Songs: Energy and Valence

library(ggplot2)
library(plotly)
library(gapminder)
library(dplyr)

## install.packages("tidytuesdayR")
tuesdata <- tidytuesdayR::tt_load(2023, week = 42)

--- Compiling #TidyTuesday Information for 2023-10-17 ----
--- There are 3 files available ---
--- Starting Download ---

    Downloading file 1 of 3: `taylor_album_songs.csv`
    Downloading file 2 of 3: `taylor_all_songs.csv`
    Downloading file 3 of 3: `taylor_albums.csv`

--- Download complete ---

taylor_album_songs <- tuesdata$taylor_album_songs

# Add a new column with color
album_name = unique(taylor_album_songs$album_name)
mycolors = c("#b9d2b5", # Taylor Swift
             "#f4cb8d", # Fearless
             "#d1b2d2", # Speak Now
             "#823549", # Red
             "#b5e9f6", # 1989
             "#847e80", # reputation
             "#f9b2d0", # Lover
             "#cfcac6", # folklore
             "#c8ae95", # evermore
             "#434961"  # Midnights
)

color_data = data.frame (album_name, color = mycolors)

taylor_album_songs = taylor_album_songs %>% left_join(color_data, by = "album_name")

data = taylor_album_songs %>%
  select(album_name, color, track_name, valence, energy)

custom_order = c("Taylor Swift", "Fearless (Taylor's Version)", "Speak Now", "Red (Taylor's Version)", "1989", "reputation", "Lover", "folklore", "evermore", "Midnights")
data$album_name = factor(data$album_name, levels = custom_order)

fig = plot_ly(data = data, x = ~energy, y = ~valence,
               color =~album_name,
               colors=mycolors,
               marker = list(size = 10),
               hovertemplate = ~paste("Track Name: ", track_name,
                             "<br>Album: ", album_name,
                             "<br>Energy: ", energy,
                             "<br>Valence: ", valence,
                             '<extra></extra>')
)

# Create text annotation
text_annotation <- list(
  x = 1.4,  # X-coordinate where you want to place the text
  y = -.2, # Y-coordinate where you want to place the text (below the plot)
  text = "<i><b>Valence</b> is musical positiveness conveyed by a track. <br>Tracks with high valence sound more positive (happy, cheerful).<br><b>Energy</b> represents represents a perceptual measure of intensity and activity.</i>",
  showarrow = FALSE,
  xref = "paper",  # x-coordinate reference is the entire plot area
  yref = "paper",  # y-coordinate reference is the entire plot area
  align = "right"
)

m <- list(
  l = 50,
  r = 50,
  b = 150,
  t = 50,
  pad = 1
)

yaxis = list(
  title = 'Spotify Valence Score (0.0 to 1.0)',
  automargin = TRUE,
  titlefont = list(size=16)
)

xaxis = list(
  title = 'Spotify Energy Score (0.0 to 1.0)',
  automargin = TRUE,
  titlefont = list(size=16)
)

fig = fig %>% layout(title = 'Taylor Swift Songs: Energy and Valence', 
                     plot_bgcolor = "#ffffff", 
                     autosize = F,
                     width = 800,
                     height = 800,
                     margin = m,
                     xaxis = xaxis, 
                     yaxis = yaxis, 
                     legend = list(title=list(text='Album')),
                     annotations = text_annotation,
                     font = list(family = "Courier New",
                                 size = 12))

Warning: Specifying width/height in layout() is now deprecated.
Please specify in ggplotly() or plot_ly()

fig

No trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plotly.com/r/reference/#scatter
No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode
Warning: Ignoring 3 observationsNo trace type specified:
  Based on info supplied, a 'scatter' trace seems appropriate.
  Read more about this trace type -> https://plotly.com/r/reference/#scatter
No scatter mode specifed:
  Setting the mode to markers
  Read more about this attribute -> https://plotly.com/r/reference/#scatter-mode
Warning: Ignoring 3 observations